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publications

(57)   

• Improving Object Detection Performance with Genetic Programming
  Mengjie Zhang International Journal on Artificial Intelligence Tools16(5):849--873October2007.
  to networks function, fitness neural object learning, programming, size, genetic program two-phase target algorithms, recognition, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Genetic Programming for Object Detection: Improving Fitness Functions and Optimising Training Data
  Mengjie Zhang and Malcolm Lett The IEEE Intelligent Informatics Bulletin7(1):12--21December2006.
  to computing, function, fitness data object classification, training localisation, programming, genetic evolutionary detection, algorithms, recognition, by brazovayeye on Jun 19, 2008, 5:46 PM
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• Using Gaussian distribution to construct fitness functions in genetic programming for multiclass object classification
  Mengjie Zhang and Will Smart Pattern Recognition Letters27(11):1266--1274August2006. Evolutionary Computer Vision and Image Understanding .
  to Fitness Probability function, programming, Multiclass genetic classification detection, algorithms, recognition, based Object by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Improving Fitness Function and Optimising Training Data in GP for Object Detection
  Mengjie Zhang and Malcolm Lett CS-TR-06-8. Computer Science, Victoria University of Wellington, New Zealand, (2006)
  to training Fitness function, programming, genetic detection, object algorithms, recognition, examples, classification, localisation by brazovayeye on Jun 19, 2008, 5:46 PM
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• GAPS: A Genetic Programming System
  Du Zhang and Michael D. Kramer International Journal on Artificial Intelligence Tools12(2):187--206June 20032003.
  to Evolutionary programming, operations, introns fitness genetic evaluation, GP algorithms, computation, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• A quantitative study of neutrality in GP boolean landscapes
  Leonardo Vanneschi and Yuri Pirola and Philippe Collard GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, 1, page895--902. Seattle, Washington, USA, ACM Press, 8-12 July2006.
  to neutrality, programming, measures, fitness performance genetic complexity even measures algorithms, landscapes, parity, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming
  Marco Tomassini and Leonardo Vanneschi and Philippe Collard and Manuel Clergue Evolutionary Computation13(2):213--239Summer2005.
  to distance programming, fitness difficulty, program genetic problem correlation algorithms, landscapes, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Designing safe, profitable automated stock trading agents using evolutionary algorithms
  Harish Subramanian and Subramanian Ramamoorthy and Peter Stone and Benjamin J. Kuipers GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2, page1777--1784. Seattle, Washington, USA, ACM Press, 8-12 July2006.
  to programming, finance, Applications, fitness genetic algorithms, evaluation Real-World by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Effective Fitness as an Alternative Paradigm for Evolutionary Computation II: Examples and Applications
  C. R. Stephens and J. Mora Vargas Genetic Programming and Evolvable Machines2(1):7--32March2001.
  to equations, fitness landscape, effective evolution genotype-phenotype genetic fitness, induced algorithms, symmetry breaking map, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Effective Fitness as an Alternative Paradigm for Evolutionary Computation I: General Formalism
  C. R. Stephens and J. Mora Vargas Genetic Programming and Evolvable Machines1(4):363--378October2000.
  to equations, fitness landscape, effective evolution genotype-phenotype genetic fitness, induced algorithms, symmetry breaking map, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Code Growth, Explicitly Defined Introns, and Alternative Selection Schemes
  Peter W. H. Smith and Kim Harries Evolutionary Computation6(4):339--360Winter1998.
  to linear programming, fitness parsimony, genetic introns, encoding selection, bloat, algorithms, by brazovayeye and 2 other people on Jun 19, 2008, 5:46 PM
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• The Fast Evaluation Strategy for Evolvable Hardware
  Mehrdad Salami and Tim Hendtlass Genetic Programming and Evolvable Machines6(2):139--162June2005.
  to hardware hardware, fitness algorithm, genetic evaluation, evolutionary evolvable algorithms, fast by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Principles in the Evolutionary Design of Digital Circuits-Part II
  Julian F. Miller and Dominic Job and Vesselin K. Vassilev Genetic Programming and Evolvable Machines1(3):259--288July2000.
  to computing, fitness reasoning, design, evolvable extraction landscapes, digital principle programming, hardware, genetic evolutionary circuit circuits, algorithms, case based by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Mining Predicate Association Rule by Gene Expression Programming
  Jie Zuo and Changjie Tang and Tianqing Zhang Advances in Web-Age Information Management, Third International Conference, WAIM 2002, volume2419ofLecture Notes in Computer Science, page92--103. Beijing, China, Springer, 11-13 August2002.
  to expression Fitness gene programming, association genetic Predicate Chromosome, algorithms, rule, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Adaptive Fitness Functions for Dynamic Growing/Pruning of Program Trees
  Byoung-Tak Zhang and Heinz Mühlenbein Advances in Genetic Programming 2, chapter 12, MIT Press, Cambridge, MA, USA, (1996)
  to functions adaptive fitness minimum trees, neural (MDL), programming, Occam's description genetic Razor, length algorithms, by brazovayeye on Jun 19, 2008, 5:35 PM
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• A Study of Good Predecessor Programs for Reducing Fitness Evaluation Cost in Genetic Programming
  Huayang Xie and Mengjie Zhang and Peter Andreae CS-TR-06-3. Computer Science, Victoria University of Wellington, New Zealand, (2006)
  to predecessor Fitness programming, genetic evaluation, programs, good algorithms, population clustering by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Crossover Context in Page-based Linear Genetic Programming
  G. C. Wilson and M. I. Heywood IEEE CCECE 2002: IEEE Canadian Conference on Electrical and Computer Engineering, 2, page809--814. IEEE Press, 12-15 May2002.
  to fitness simple trail, strategies, change, effective crossover programming, search sequences, operator, algorithms, instructions, Learning, problems, memories, Strategy strategy (artificial code learning Mateo San register intelligence), genetic artificial ants, based by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Digital Circuit Evolution and Fitness Landscapes
  Vesselin K. Vassilev and Julian F. Miller and Terence C. Fogarty Proceedings of the Congress on Evolutionary Computation, 2, Mayflower Hotel, Washington D.C., USA, IEEE Press, 6-9 July1999.
  to evolution, fitness optimisation, genotype engineering digital landscapes, characteristics, search, programmable sequences, idealised connectivity, evolutionary alphabets, computation, field-programmable problems, cell sequences array, correlation arrays, logic gate field functionality, combinatorial problem, circuits, circuit representation, model, optimisation by brazovayeye on Jun 19, 2008, 5:35 PM
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• Evolutionary synthesis of digital filter structures using genetic programming
  Kazuyoshi Uesaka and Masayuki Kawamata IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing50(12):977--983December2003.
  to equations, fitness matrices, digital function response subroutines, sensitivity, programming, method, errors, automatically evolutionary algorithms, synthesis filters, fourth-order wordlength transfer roundoff effects, defined measure, matrix IIR global low-coefficient functions, optimization, S-expressions, low-output difference computability, infinite-impulse structures, filter, genetic representation, noise, filter by brazovayeye on Jun 19, 2008, 5:35 PM
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• Synthesis of low-sensitivity second-order digital filters using genetic programming with automatically defined functions
  Kazuyoshi Uesaka and Masayuki Kawamata IEEE Signal Processing Letters7(4):83--85April2000.
  to coefficient defined sensitivity measure, fitness IIR magnitude functions, S-expressions, digital sensitivity, programming, method, filter, second-order genetic automatically algorithms, synthesis low ADF filter filters, by brazovayeye on Jun 19, 2008, 5:35 PM
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